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Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.
Dan Linstedt, the creator of the method, describes the resulting database as follows: "The Data Vault Model is a detail oriented, historical tracking and uniquely linked set of normalized tables that support one or more functional areas of business. It is a hybrid approach encompassing the best of breed between 3rd normal form (3NF) and star ...
The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. [2] The star schema gets its name from the physical model's [3] resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points.
Example of a star schema; the central table is the fact table. In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation ...
The dimensional model is built on a star-like schema or snowflake schema, with dimensions surrounding the fact table. [3] [4] To build the schema, the following design model is used: Choose the business process; Declare the grain; Identify the dimensions; Identify the fact; Choose the business process
Perhaps we could add a SQL code sample and a simple ERD to demonstrate a snowflake schema? I think it would be a good idea to coordinate the example with the star schema article, to show a snowflake schema version of the same example given over there. SqlPac 20:33, 27 June 2008 (UTC) Is the join on Store_ID required in the sample given?
Examples of denormalization techniques include: "Storing" the count of the "many" elements in a one-to-many relationship as an attribute of the "one" relation; Adding attributes to a relation from another relation with which it will be joined; Star schemas, which are also known as fact-dimension models and have been extended to snowflake schemas
Unlike the star schema (dimensional modelling) and the classical relational model (3NF), data vault and anchor modeling are well-suited for capturing changes that occur when a source system is changed or added, but are considered advanced techniques which require experienced data architects. [2]